Exercise 2: Plot (some of) the data in a calendar layout
What do you think Melbourne will be liek in 2050? Can you imagine what your life will be like, if you are still living here? What will be different, what will be the same?
Be energy-wise, for a greener future. Climate change is consistently in the news. The consequences for Melbourne are more extreme high temperatures and drought. Individuals can play a big role in mitigating the extremes of the future, if they know how their actions contribute to the world as a whole. All of Melbourne households now have smart meters, which report the energy use every 30 minutes.
Business analytics involves mathematics, computing and data. This lab exercise has a little of both. For the coding part, you will want to pretend you are a master cook, fashion designer, computer repairer or motor mechanic: copy, pull apart and put together again.
We will show you how to download the smart meter data for your household, wrangle it into shape, and then how to make plots to explore household energy use. What times of day does the household use the most energy, or time of year? Is it related to the weather, with air conditioner or heater usage, or special events, like washing and drying clothes the night before a holiday trip, or dinner parties with friends. We will compare the usage across different households. All the tools used are open source software that will be available to you into the future.
Point your web browser to this site: https://compare.energy.vic.gov.au. How can you earn $50 from your energy data?
What’s a smart meter? Take a look at the web site http://www.smartmeters.vic.gov.au/# How many smart meters have been installed across Victoria?
Materials for the workshop can be downloaded from https://github.com/Monash-BDCD/energy. It will download and unzip onto your computer with the name “energy-master”, by default. Change it to “energy”.
There are several files that will download:
lab.Rmd (This is an Rmarkdown file, that has code and explanations, to compile into a document.)lab.html (This has the instructions for you to follow.)data is a directory containing some sample energy filesenergy_app contains files to make a web appenergy.Rproj An R project, clicking on this will open RStudio (and R) on your computer.Data collected by downloading Di’s (and friend of hers) electricity usage data as recorded by the household smart meter. Details on how to do this are (THIS IS ONLY IF YOU WANT TO COLLECT YOUR OWN HOUSEHOLD’S DATA):
Maybe after this workshop, you can do your own household, upload it to the compare suppliers site, claim your $50 (and get your parent to pay you this for your efforts), and possibly get a better deal on household energy costs.
Cheat sheets are provided for:
Read in Di’s energy data. Look at the format of the data, and then rearrange it to a tidier format.
## # A tibble: 10 x 55
## id date d1 d2 d3 d4 d5 d6 d7 d8 d9 d10
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 200 meter1 NA NA NA NA NA NA 30 NA NA NA
## 2 300 20171… 0 0 0 0 0 0 0 0 0 0
## 3 300 20171… 0 0 0 0 0 0 0 0 0 0
## 4 300 20171… 0 0 0 0 0 0 0 0 0 0
## 5 300 20171… 0 0 0 0 0 0 0 0 0 0
## 6 300 20171… 0 0 0 0 0 0 0 0 0 0
## 7 300 20171… 0 0 0 0 0 0 0 0 0 0
## 8 400 1 43 NA NA NA NA NA NA NA NA NA
## 9 400 44 44 NA 89 NA NA NA NA NA NA NA
## 10 400 45 48 NA NA NA NA NA NA NA NA NA
## # … with 43 more variables: d11 <dbl>, d12 <dbl>, d13 <dbl>, d14 <dbl>,
## # d15 <dbl>, d16 <dbl>, d17 <dbl>, d18 <dbl>, d19 <dbl>, d20 <dbl>,
## # d21 <dbl>, d22 <dbl>, d23 <dbl>, d24 <dbl>, d25 <dbl>, d26 <dbl>,
## # d27 <dbl>, d28 <dbl>, d29 <dbl>, d30 <dbl>, d31 <dbl>, d32 <dbl>,
## # d33 <dbl>, d34 <dbl>, d35 <dbl>, d36 <dbl>, d37 <dbl>, d38 <dbl>,
## # d39 <dbl>, d40 <dbl>, d41 <dbl>, d42 <dbl>, d43 <dbl>, d44 <dbl>,
## # d45 <dbl>, d46 <dbl>, d47 <dbl>, d48 <dbl>, stuff1 <chr>,
## # stuff2 <chr>, stuff3 <chr>, stuff4 <chr>, stuff5 <chr>Here’s the wrangling, 🏃♀, and new format:
## # A tibble: 15 x 9
## id date halfhour kwh wday month year dt
## <chr> <date> <dbl> <dbl> <ord> <ord> <dbl> <dttm>
## 1 300 2017-11-24 0.5 0 Fri Nov 2017 2017-11-24 12:30:00
## 2 300 2017-11-24 1 0 Fri Nov 2017 2017-11-24 13:00:00
## 3 300 2017-11-24 1.5 0 Fri Nov 2017 2017-11-24 13:30:00
## 4 300 2017-11-24 2 0 Fri Nov 2017 2017-11-24 14:00:00
## 5 300 2017-11-24 2.5 0 Fri Nov 2017 2017-11-24 14:30:00
## 6 300 2017-11-24 3 0 Fri Nov 2017 2017-11-24 15:00:00
## 7 300 2017-11-24 3.5 0 Fri Nov 2017 2017-11-24 15:30:00
## 8 300 2017-11-24 4 0 Fri Nov 2017 2017-11-24 16:00:00
## 9 300 2017-11-24 4.5 0 Fri Nov 2017 2017-11-24 16:30:00
## 10 300 2017-11-24 5 0 Fri Nov 2017 2017-11-24 17:00:00
## 11 300 2017-11-24 5.5 0 Fri Nov 2017 2017-11-24 17:30:00
## 12 300 2017-11-24 6 0 Fri Nov 2017 2017-11-24 18:00:00
## 13 300 2017-11-24 6.5 0 Fri Nov 2017 2017-11-24 18:30:00
## 14 300 2017-11-24 7 0 Fri Nov 2017 2017-11-24 19:00:00
## 15 300 2017-11-24 7.5 0 Fri Nov 2017 2017-11-24 19:30:00
## # … with 1 more variable: work <chr>
With your new app, XXX
Each group needs to provide to the instructor: